TPU

“TPU” can refer to several things depending on context, but in technology and computing, TPU most commonly stands for:

⚙️ Tensor Processing Unit
A Tensor Processing Unit (TPU) is a type of application-specific integrated circuit (ASIC) developed by Google specifically for accelerating machine learning workloads, especially those built with TensorFlow.

✅ Key Features of TPUs:
Optimized for Matrix Math: Designed to accelerate tensor operations like matrix multiplication, which are common in neural networks.

High Throughput: Offers higher performance per watt compared to general-purpose GPUs or CPUs for specific ML tasks.

Used in Google Cloud: Google offers TPUs as part of their Cloud AI infrastructure.

Supported by TensorFlow: You can run models on TPUs with minimal changes to TensorFlow code.

📌 TPU vs GPU vs CPU
Feature TPU GPU CPU
Use Case ML model training/inference ML, graphics, general compute General-purpose processing
Speed (ML) Very fast (ML-specific) Fast Slower
Energy Use Efficient Moderate Less efficient (for ML)
Flexibility Specialized Flexible Very flexible